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New Open-Source Analyses of Transit Job Access and Transit Ridership

  • Author(s): Boarnet, Marlon G.;
  • Flores Moctezuma, David;
  • Gross, James
  • et al.

Published Web Location

https://doi.org/10.7922/G2862DSW
The data associated with this publication are available at:
https://doi.org/10.7910/DVN/S2WRF2
Abstract

This research project examines the link between job access and stop/station level transit ridership. Job access, following recent literature, is measured as the number of jobs that can be reached within a 30-minute transit travel time, including transfers and walk time to access jobs once exiting a transit station. Cumulative opportunity job access measures of this sort—i.e., the number of jobs that can be reached within 30 minutes—have become common in the recent access literature, and those measures have often focused on access via transit. Yet there have been few studies that examine the link between transit job access and transit ridership, and of those none that examine the link at a station or stop level. This study uses station and stop level ridership data for the Los Angeles Metro bus and rail system and the BART rail system in the San Francisco Bay Area. The research team calculated transit job access as jobs that can be reached within 30 minutes, using the Remix software tool. Regression analysis of 1,000 randomly selected Los Angeles bus stops reveals a robust relationship between stop-level ridership and job access. The association between transit job access and bus stop ridership (embarkations and disembarkations at the stop) is statistically significant. Converting that association into an elasticity, if the number of jobs accessible within 30-minutes were to increase by 1 percent, on average stop-level ridership would increase between 0.6 to 0.8 percent. The same association, with similar magnitudes, exists for Metro rail stations and BART rail stations, but due the smaller sample sizes, those relationships are not statistically significant when control variables are added to the regression. The findings show that job access is closely related to ridership at the bus stop level, suggesting transit agencies can increase job access by increasing bus frequency, reducing transfers, siting lines that connect job concentrations to residents, and by improving bus stop/rail station access/egress times.

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